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https://api.github.com/repos/huggingface/transformers/issues/10635 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10635/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10635/comments | https://api.github.com/repos/huggingface/transformers/issues/10635/events | https://github.com/huggingface/transformers/pull/10635 | 828,240,892 | MDExOlB1bGxSZXF1ZXN0NTkwMDcwOTMx | 10,635 | Document Trainer limitation on custom models | {
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As discussed in #10629, documenting the limitations of the `Trainer` when working with custom models. | {
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https://api.github.com/repos/huggingface/transformers/issues/10634 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10634/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10634/comments | https://api.github.com/repos/huggingface/transformers/issues/10634/events | https://github.com/huggingface/transformers/issues/10634 | 828,227,350 | MDU6SXNzdWU4MjgyMjczNTA= | 10,634 | Issues with Multi-GPU | {
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"Had to remove the following:\r\n\r\n```\r\ndevice = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\r\nn_gpus = torch.cuda.device_count()\r\nif n_gpus > 1:\r\n model = nn.DataParallel(model)\r\nmodel.to(device)\r\n```\r\n\r\nThen everything is running for torch==1.7.1 for both GPUs. So `Trainer... | 1,615 | 1,615 | 1,615 | NONE | null | - `transformers` version: 4.3.3
- Platform: Linux-4.15.0-132-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.8.0 (True)
- Tensorflow version (GPU?): 2.3.0 (True)
- Using GPU in script?: Yes, multi GeForce RTX 2080 Ti GPUs
- Using distributed or parallel set-up in script... | {
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https://api.github.com/repos/huggingface/transformers/issues/10633 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10633/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10633/comments | https://api.github.com/repos/huggingface/transformers/issues/10633/events | https://github.com/huggingface/transformers/pull/10633 | 828,167,271 | MDExOlB1bGxSZXF1ZXN0NTkwMDA1MjM0 | 10,633 | Extend trainer logging for sm | {
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adds a helper function to `logging.py` to add a native logging handler if needed (`add_handler`). Adds in the `Trainer` a logging `StreamHandler(sys.stdout)` with `sys.stdout` when training is run on sagemaker to forward logs. | {
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https://api.github.com/repos/huggingface/transformers/issues/10632 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10632/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10632/comments | https://api.github.com/repos/huggingface/transformers/issues/10632/events | https://github.com/huggingface/transformers/pull/10632 | 828,116,610 | MDExOlB1bGxSZXF1ZXN0NTg5OTU5MTkz | 10,632 | Ensure metric results are JSON-serializable | {
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Metrics returned from numpy (with an `np.mean()` for instance) are not real Python floats but `np.float32` (or other type) objects that are not serializable. This causes problems when the metrics are saved in JSON format in the `Trainer`, for instance when using `load_best_model_at_end`. This... | {
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https://api.github.com/repos/huggingface/transformers/issues/10631 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10631/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10631/comments | https://api.github.com/repos/huggingface/transformers/issues/10631/events | https://github.com/huggingface/transformers/issues/10631 | 828,054,113 | MDU6SXNzdWU4MjgwNTQxMTM= | 10,631 | Help using Speech2Text | {
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"Your speech loading code is incorrect; instead try the following:\r\n\r\n```python\r\nfrom IPython.display import Audio\r\n\r\nspeech, rate = librosa.load(filename, sr=16000)\r\nAudio(speech, rate=rate)\r\n```",
"When I run this line\r\n\r\n`processor = Speech2TextProcessor.from_pretrained(\"facebook/s2t-small-l... | 1,615 | 1,691 | 1,615 | NONE | null | Hey @patil-suraj (and anyone who can help),
Sorry, I'm still a beginner compared to the rest of the folks here so sorry if my question is a little basic.
But I'm trying to build a pipeline to manually transcribe Youtube videos (that aren't transcribed correctly by Google) and I was considering using your [model ]... | {
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https://api.github.com/repos/huggingface/transformers/issues/10630 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10630/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10630/comments | https://api.github.com/repos/huggingface/transformers/issues/10630/events | https://github.com/huggingface/transformers/issues/10630 | 827,858,299 | MDU6SXNzdWU4Mjc4NTgyOTk= | 10,630 | I get different results everytime I run run_squad.py | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,615 | 1,619 | 1,619 | NONE | null | Is it possible to have deterministic results using the run_squad.py script?
It has the set_seed() method but still, it gives different results every time I run it.
How can I get same results across all runs? | {
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https://api.github.com/repos/huggingface/transformers/issues/10629 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10629/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10629/comments | https://api.github.com/repos/huggingface/transformers/issues/10629/events | https://github.com/huggingface/transformers/issues/10629 | 827,535,935 | MDU6SXNzdWU4Mjc1MzU5MzU= | 10,629 | Using `label` in Trainer leads to TypeError | {
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"Pinging @sgugger ",
"Yes, the default data collator always change `label` to `labels` because Hugging Face models expect that argument while Hugging Face datasets usually have `label`. You can work around this by using the default data collator of PyTorch and pass it to the `Trainer`, but you should make your mo... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.0+cu101 (True)
- Tensorflow version (GPU?): 2.4.1 (True)
- Using GPU in script?: Not explicitly.
- Using distributed or parallel set-up in scrip... | {
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https://api.github.com/repos/huggingface/transformers/issues/10628 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10628/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10628/comments | https://api.github.com/repos/huggingface/transformers/issues/10628/events | https://github.com/huggingface/transformers/issues/10628 | 827,443,113 | MDU6SXNzdWU4Mjc0NDMxMTM= | 10,628 | expanduser path in Trainer | {
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"Sounds reasonable. Would you like to make a PR with this change?",
"Can do.\r\nI should expand the path in TrainingArguments right? for logging_dir also?",
"Yes, `output_dir` and `logging_dir`, preferable in the postinit of `TrainingArguments` so it's done as early as possible."
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | the `output_dir` passed to TrainingArguments is not expanded (the behaviour is probably the same for logging_dir)
### Who can help
Library:
- trainer: @sgugger
## To reproduce
Directly using os.makedirs but this is what happens in Trainer
```py
In [7]: !mkdir ~/foo
In [8]: !cd ~/foo
/mnt/beegfs/home/... | {
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https://api.github.com/repos/huggingface/transformers/issues/10627 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10627/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10627/comments | https://api.github.com/repos/huggingface/transformers/issues/10627/events | https://github.com/huggingface/transformers/issues/10627 | 827,440,372 | MDU6SXNzdWU4Mjc0NDAzNzI= | 10,627 | considering `pad_to_multiple_of` for run_mlm.py | {
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"Indeed, we could use that when the line by line option is set (otherwise there is just no padding). Would you like to make a PR with this?"
] | 1,615 | 1,617 | 1,617 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.3
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): - ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10626 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10626/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10626/comments | https://api.github.com/repos/huggingface/transformers/issues/10626/events | https://github.com/huggingface/transformers/issues/10626 | 827,371,372 | MDU6SXNzdWU4MjczNzEzNzI= | 10,626 | Average checkpoints | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,615 | 1,615 | 1,615 | NONE | null | Is it possible to average weights of several checkpoints? Some thing like https://github.com/pytorch/fairseq/blob/master/scripts/average_checkpoints.py | {
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https://api.github.com/repos/huggingface/transformers/issues/10625 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10625/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10625/comments | https://api.github.com/repos/huggingface/transformers/issues/10625/events | https://github.com/huggingface/transformers/issues/10625 | 827,318,386 | MDU6SXNzdWU4MjczMTgzODY= | 10,625 | Model "deberta-v2--xxlarge-mnli" doesn't work!!! | {
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"No, DeBERTa-v2 is not available in v4.3.3, it's only available from source as of now. Version v4.4.0 should be released end of this week or early next week, and will have DeBERTa-v2.",
"Yes, exactly what i think! Thanks Lysandre for confirming this."
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | Whenever i try to load the tokenizer by
```python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained('microsoft/deberta-v2-xxlarge-mnli')
```
it returns this issue:
```
config_class = CONFIG_MAPPING[config_dict["model_type"]]
KeyError: 'deberta-v2'
```
Is this model ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10624 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10624/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10624/comments | https://api.github.com/repos/huggingface/transformers/issues/10624/events | https://github.com/huggingface/transformers/pull/10624 | 827,065,189 | MDExOlB1bGxSZXF1ZXN0NTg5MDExODY1 | 10,624 | Copy tokenizer files in each of their repo | {
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"Love it!\r\n\r\nMaybe a good practice to link to a sample of the related commits on hf.co: for instance here https://huggingface.co/facebook/bart-base/commit/c2469fb7e666a5c5629a161f17c9ef23c85217f7",
"I think I did around 50 of them in various repos to move all the tokenizers files, so a bit hard to keep track ... | 1,615 | 1,615 | 1,615 | COLLABORATOR | null | # What does this PR do?
This PR cleans the maps in the tokenizer files to make sure each checkpoint has the proper tokenization files. This will allow us to remove custom code that mapped some checkpoints to special files (like BART using RoBERTa vocab files) and take full advantage of the versioning systems for tho... | {
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https://api.github.com/repos/huggingface/transformers/issues/10623 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10623/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10623/comments | https://api.github.com/repos/huggingface/transformers/issues/10623/events | https://github.com/huggingface/transformers/issues/10623 | 827,011,734 | MDU6SXNzdWU4MjcwMTE3MzQ= | 10,623 | Invalid pytorch_model.bin for TAPAS-large | {
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"Hi, not sure why this happens, cc @julien-c.\r\n\r\nA workaround is to load the model using `model = TapasModel.from_pretrained(\"google/tapas-base\")` and then use `model.save_pretrained(\"./\")` to save the `config.json` and `pytorch_model.bin` file to a local directory. ",
"I don't remember how those models w... | 1,615 | 1,615 | 1,615 | NONE | null | Hi,
I was downloading `google/tapas-large` binaries from [HF models](https://huggingface.co/google/tapas-large/tree/main) and for pytorch_model.bin, a zip file was getting downloaded which is not a `bin` file like other models.
folder structure is like - `archive/data/.*File`, `archive/data.pkl` ,` archive/version.... | {
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https://api.github.com/repos/huggingface/transformers/issues/10622 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10622/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10622/comments | https://api.github.com/repos/huggingface/transformers/issues/10622/events | https://github.com/huggingface/transformers/issues/10622 | 827,003,569 | MDU6SXNzdWU4MjcwMDM1Njk= | 10,622 | wav2vec2: adding single-char tokens to tokenizer causes tokenization mistakes | {
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"My workaround right now is to keep a reference to the original `tokenizer.unique_no_split_tokens` before adding tokens then restoring it afterwards:\r\n\r\n```python\r\nfrom transformers import Wav2Vec2Processor\r\n\r\ntokenizer = Wav2Vec2Processor.from_pretrained('facebook/wav2vec2-base').tokenizer\r\nunique_no_s... | 1,615 | 1,620 | 1,620 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Linux-5.8.0-44-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.0 (True)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: N/A
- Using distributed or parallel set-up in script?: N/A
### W... | {
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https://api.github.com/repos/huggingface/transformers/issues/10621 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10621/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10621/comments | https://api.github.com/repos/huggingface/transformers/issues/10621/events | https://github.com/huggingface/transformers/pull/10621 | 826,890,988 | MDExOlB1bGxSZXF1ZXN0NTg4ODU1ODE3 | 10,621 | Fixes an issue in `text-classification` where MNLI eval/test datasets are not being preprocessed. | {
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In https://github.com/huggingface/transformers/commit/dfd16af8322788e6dd58e8396e0d6f2f5312bf99 for `run_glue.py`, `{train|eval|test}_dataset` was split out and preprocessed individually. However, this misses `datasets["{validation|test}_mismatched"]` which is appended to the `{eval|test}_datase... | {
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https://api.github.com/repos/huggingface/transformers/issues/10620 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10620/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10620/comments | https://api.github.com/repos/huggingface/transformers/issues/10620/events | https://github.com/huggingface/transformers/issues/10620 | 826,890,321 | MDU6SXNzdWU4MjY4OTAzMjE= | 10,620 | MNLI eval/test dataset is not being preprocessed in `run_glue.py` | {
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"Fixed by #10621 \r\nThanks for flagging and fixing :-)"
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.0.dev0
- Platform: Linux-4.9.0-14-amd64-x86_64-with-debian-9.13
- Python version: 3.6.10
- PyTorch ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/10619 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10619/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10619/comments | https://api.github.com/repos/huggingface/transformers/issues/10619/events | https://github.com/huggingface/transformers/issues/10619 | 826,887,608 | MDU6SXNzdWU4MjY4ODc2MDg= | 10,619 | wav2vec2: `convert_tokens_to_string` contracts legitimately repeated characters | {
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"Can you try this?\r\n\r\n```python\r\nfrom transformers import Wav2Vec2Processor\r\n\r\ntokenizer = Wav2Vec2Processor.from_pretrained('facebook/wav2vec2-base').tokenizer\r\ntokenizer.decode(tokenizer('CARRY').input_ids, group_tokens=False)\r\n# CARRY\r\n```\r\n\r\nBecause we need to decode the predicted tokens wit... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Linux-5.8.0-44-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.0 (True)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: N/A
- Using distributed or parallel set-up in script?: N/A
### W... | {
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https://api.github.com/repos/huggingface/transformers/issues/10618 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10618/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10618/comments | https://api.github.com/repos/huggingface/transformers/issues/10618/events | https://github.com/huggingface/transformers/issues/10618 | 826,764,486 | MDU6SXNzdWU4MjY3NjQ0ODY= | 10,618 | Run_qa crashes because of parser = HfArgumentParser((ModelArguments, DataTrainingArguments, TrainingArguments)) | {
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"This is weird and linked to your environment somehow. \r\n@stas00 Was this the error you encountered when `dataclasses` is installed in Python 3.7 or was it a different one?",
"no, that was not that error. I tested `run_qa.py` w/ dataclasses on py38 and it didn't fail.\r\n\r\nthe datasets error was: `AttributeEr... | 1,615 | 1,615 | 1,615 | NONE | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: linux
- Python version:3.7, 3.8, 3.9 reproed across all three
- PyTorch version (GPU?): 1.7, tried 1.8 with same behavior
- Tensorflow version (GPU?):N/A
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: Yes 2 gpu
###... | {
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https://api.github.com/repos/huggingface/transformers/issues/10617 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10617/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10617/comments | https://api.github.com/repos/huggingface/transformers/issues/10617/events | https://github.com/huggingface/transformers/issues/10617 | 826,723,391 | MDU6SXNzdWU4MjY3MjMzOTE= | 10,617 | Request: Ignore Dataset transforms when iterating to the most recent checkpoint when resuming training | {
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"This is already there :-) Just pass along `--ignore_data_skip` in your script or `ignore_data_skip=True` in your `TrainingArguments`.",
"Wow, that was fast! :) \r\n\r\nThat loads the model from the checkpoint and advances the dataset to the next sample that would have been trained in the original run?\r\n\r\nFro... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | # 🚀 Feature request
It'd be great if, when resuming training from a checkpoint and using a Dataset with a format/transform function applied, the dataset's format/transform function could be ignored while iterating up to the last checkpoint step.
@lhoestq @sgugger
## Motivation
I doubt it's much of an issu... | {
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https://api.github.com/repos/huggingface/transformers/issues/10616 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10616/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10616/comments | https://api.github.com/repos/huggingface/transformers/issues/10616/events | https://github.com/huggingface/transformers/issues/10616 | 826,717,478 | MDU6SXNzdWU4MjY3MTc0Nzg= | 10,616 | changing ".view()" to ".reshape()" for pytorch | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,615 | 1,619 | 1,619 | NONE | null | New Version of PyTorch uses ".reshape()" instead of ".view()".
There might be some issue if still using ".view()". | {
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https://api.github.com/repos/huggingface/transformers/issues/10615 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10615/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10615/comments | https://api.github.com/repos/huggingface/transformers/issues/10615/events | https://github.com/huggingface/transformers/pull/10615 | 826,655,485 | MDExOlB1bGxSZXF1ZXN0NTg4NjQwMTU4 | 10,615 | Fix tests of TrainerCallback | {
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When introducing the `report_to` argument, I must have messed something up. Bottomline is that the tests of `TrainerCallback` can fail depending on what is installed in the env (TensorBoard for instance), this PR fixes that. | {
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https://api.github.com/repos/huggingface/transformers/issues/10614 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10614/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10614/comments | https://api.github.com/repos/huggingface/transformers/issues/10614/events | https://github.com/huggingface/transformers/issues/10614 | 826,541,541 | MDU6SXNzdWU4MjY1NDE1NDE= | 10,614 | Not able to convert T5 tf checkpoints | {
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"It seems that T5 was added to the conversion scripts two months ago in https://github.com/huggingface/transformers/pull/9654 as you've mentioned.\r\n\r\nHowever, in your error there is no mention of \"t5\":\r\n```\r\nValueError: --model_type should be selected in the list [bert, gpt, gpt2, transfo_xl, xlnet, xlm]\... | 1,615 | 1,619 | 1,619 | NONE | null | Hi,
I was trying to convert some tf checkpoints for T5 into PyTorch using ```transformers-cli convert```, and am getting the following error:
> Traceback (most recent call last):
File "/home/william18026/miniconda3/bin/transformers-cli", line 32, in <module>
service.run()
File "/home/william18026/minicon... | {
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https://api.github.com/repos/huggingface/transformers/issues/10613 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10613/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10613/comments | https://api.github.com/repos/huggingface/transformers/issues/10613/events | https://github.com/huggingface/transformers/issues/10613 | 826,298,015 | MDU6SXNzdWU4MjYyOTgwMTU= | 10,613 | OOM issues with save_pretrained models | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,615 | 1,628 | 1,619 | NONE | null | Posted this issue to the HuggingFace forums without a response.
Having a weird issue with DialoGPT Large model deployment. From PyTorch 1.8.0 and Transformers 4.3.3 using model.save_pretrained and tokenizer.save_pretrained, the exported pytorch_model.bin is almost twice the size of the model card repo and results in... | {
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https://api.github.com/repos/huggingface/transformers/issues/10612 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10612/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10612/comments | https://api.github.com/repos/huggingface/transformers/issues/10612/events | https://github.com/huggingface/transformers/issues/10612 | 826,204,473 | MDU6SXNzdWU4MjYyMDQ0NzM= | 10,612 | Implementing efficient self attention in T5 | {
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"There are already some PRs regarding these models, I'm working on adding the Linformer (#10587), there's also a PR for the Performer (#9325, see further down the thread - people can already train T5 with Performer). "
] | 1,615 | 1,615 | null | CONTRIBUTOR | null | # 🌟 New model addition
My teammates and I (including @ice-americano) would like to use efficient self attention methods such as Linformer, Performer and Nystromformer
## Model description
These new methods serve as approximations of regular attention, but reduce complexity from quadratic in the inputs to line... | {
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https://api.github.com/repos/huggingface/transformers/issues/10611 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10611/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10611/comments | https://api.github.com/repos/huggingface/transformers/issues/10611/events | https://github.com/huggingface/transformers/pull/10611 | 826,154,820 | MDExOlB1bGxSZXF1ZXN0NTg4MTc4ODkz | 10,611 | split seq2seq script into summarization & translation | {
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"cc @stas00 `run_seq2seq` is left as is for now. At some point, if your tests migrate from that script to either the new ones or another one, we will remove it.",
"> cc @stas00 `run_seq2seq` is left as is for now. At some point, if your tests migrate from that script to either the new ones or another one, we will... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | keeping the original script for tests cc @stas00
fix #10164 | {
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https://api.github.com/repos/huggingface/transformers/issues/10610 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10610/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10610/comments | https://api.github.com/repos/huggingface/transformers/issues/10610/events | https://github.com/huggingface/transformers/pull/10610 | 826,120,770 | MDExOlB1bGxSZXF1ZXN0NTg4MTQ4NTE0 | 10,610 | Trigger add sm information | {
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https://api.github.com/repos/huggingface/transformers/issues/10609 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10609/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10609/comments | https://api.github.com/repos/huggingface/transformers/issues/10609/events | https://github.com/huggingface/transformers/issues/10609 | 825,909,479 | MDU6SXNzdWU4MjU5MDk0Nzk= | 10,609 | SortedDL for contiguous LM | {
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"This issue is more suited for the forum, but maybe @sgugger has some hints to share!",
"I'm not sure what you would want to sort a single text stream. The `Trainer` supports `--group_by_length` but that's when you have multiple texts.\r\n\r\nNote that `DataCollatorForLanguageModeling` only performs random maskin... | 1,615 | 1,616 | 1,616 | NONE | null | Hi there,
I am currently implementing LM re-training of a RoBERTa model using the `Trainer` API. Since I have a huge training corpus, I was wondering if there is a functionality in the `Trainer` or the corresponding `DataCollatorForLanguageModeling` that allows for sorted batching as in `fastai`?
More precisely, I... | {
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https://api.github.com/repos/huggingface/transformers/issues/10608 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10608/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10608/comments | https://api.github.com/repos/huggingface/transformers/issues/10608/events | https://github.com/huggingface/transformers/pull/10608 | 825,886,530 | MDExOlB1bGxSZXF1ZXN0NTg3OTM4MzYx | 10,608 | Image feature extractor design | {
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Here we can discuss how to design the `ImageFeatureExtractor` class, and the `ViTFeatureExtractor` subclass.
The hierarchy looks as follows:
`FeatureExtractorMixin` -> `ImageFeatureExtractor` -> `ViTFeatureExtractor`. The `FeatureExtractorMixin` defines common properties among `SequenceF... | {
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https://api.github.com/repos/huggingface/transformers/issues/10607 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10607/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10607/comments | https://api.github.com/repos/huggingface/transformers/issues/10607/events | https://github.com/huggingface/transformers/issues/10607 | 825,722,416 | MDU6SXNzdWU4MjU3MjI0MTY= | 10,607 | Can't load config for hosted model, works when downloaded | {
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"Hello! I can do `model = AutoModelForMaskedLM.from_pretrained(\"EMBEDDIA/sloberta\")` without any issues on my end.\r\n\r\nCould it be linked to a connection issue?\r\n\r\n```py\r\n>>> from transformers import AutoModelForMaskedLM\r\n>>> model = AutoModelForMaskedLM.from_pretrained(\"EMBEDDIA/sloberta\")\r\nDownlo... | 1,615 | 1,615 | 1,615 | NONE | null | I have recently (19 hours ago) uploaded a new model to huggingface: https://huggingface.co/EMBEDDIA/sloberta
When attempting to load it with `model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/sloberta")` I get the following error:
```
Traceback (most recent call last):
File "/home/mulcar/.conda/envs/tra... | {
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https://api.github.com/repos/huggingface/transformers/issues/10606 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10606/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10606/comments | https://api.github.com/repos/huggingface/transformers/issues/10606/events | https://github.com/huggingface/transformers/pull/10606 | 825,568,203 | MDExOlB1bGxSZXF1ZXN0NTg3NjQ5NzU3 | 10,606 | [M2M100] remove final_logits_bias | {
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M2M100 does not need `final_logits_bias`, this PR removes it from the `M2M100ForConditionalGeneration` | {
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https://api.github.com/repos/huggingface/transformers/issues/10605 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10605/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10605/comments | https://api.github.com/repos/huggingface/transformers/issues/10605/events | https://github.com/huggingface/transformers/pull/10605 | 825,562,298 | MDExOlB1bGxSZXF1ZXN0NTg3NjQ0NDU3 | 10,605 | Fix cross-attention head mask for Torch encoder-decoder models | {
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"Hi @patrickvonplaten & @patil-suraj, my PR does not pass one test, however, I am not able to reproduce this error on my local (I can't even find the file at `src/transformers/models/new_enc_dec/modeling_new_enc_dec.py` in the repo, which is the one where should be a problem with a copy inconsistency)",
"Hi @stan... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | 1. This PR fixes head masking for the cross-attention module in the following models:
- BART,
- Blenderbot,
- Blenderbot_small,
- FSMT,
- LED,
- M2M_100,
- Marian,
- MBart,
- Pegasus.
- T5
2. This PR also contains slight changes in docstrings so that it will be clear that `head_mask` is related to the co... | {
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https://api.github.com/repos/huggingface/transformers/issues/10604 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10604/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10604/comments | https://api.github.com/repos/huggingface/transformers/issues/10604/events | https://github.com/huggingface/transformers/pull/10604 | 825,451,258 | MDExOlB1bGxSZXF1ZXN0NTg3NTQ0MTI0 | 10,604 | fix flaky m2m100 test | {
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The `test_retain_grad_hidden_states_attentions` test is sometimes failing for `M2M100`, with the error
` AttributeError: 'NoneType' object has no attribute 'retain_grad'`
This is because of `layerdrop` sometimes a layer is skipped and the `encoder_attenion/decoder_attentions/cross_attent... | {
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https://api.github.com/repos/huggingface/transformers/issues/10603 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10603/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10603/comments | https://api.github.com/repos/huggingface/transformers/issues/10603/events | https://github.com/huggingface/transformers/issues/10603 | 825,414,757 | MDU6SXNzdWU4MjU0MTQ3NTc= | 10,603 | AlbertForSequenceClassification random output | {
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"Hello! You're loading a model called `albert_chinese_base`; my guess is that this model only contains the base transformer model and not the sequence classification head that you need.\r\n\r\nDoes that make sense? You should use a model fine-tuned on sequence classification, and not a base model, if you want to do... | 1,615 | 1,619 | 1,619 | NONE | null | I use AlbertForSequenceClassification interface as follows:
`import torch
from transformers import BertTokenizer,AlbertConfig,AlbertForSequenceClassification
import numpy
pretrained = "./albert_chinese_base"
tokenizer = BertTokenizer.from_pretrained(pretrained)
config = AlbertConfig.from_json_file('./albert_chin... | {
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https://api.github.com/repos/huggingface/transformers/issues/10602 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10602/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10602/comments | https://api.github.com/repos/huggingface/transformers/issues/10602/events | https://github.com/huggingface/transformers/pull/10602 | 825,353,100 | MDExOlB1bGxSZXF1ZXN0NTg3NDU3NzQz | 10,602 | [examples template] added max_sample args and metrics changes | {
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"Ya @stas00,\nActually I figured that and tested visually with the example tamplate not the model template"
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | # What does this PR do?
This PR adds the same as https://github.com/huggingface/transformers/pull/10551 and https://github.com/huggingface/transformers/pull/10436 to the cookie-cutter template.
Fixes #10423
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other che... | {
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https://api.github.com/repos/huggingface/transformers/issues/10601 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10601/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10601/comments | https://api.github.com/repos/huggingface/transformers/issues/10601/events | https://github.com/huggingface/transformers/pull/10601 | 825,203,794 | MDExOlB1bGxSZXF1ZXN0NTg3MzIwMDIy | 10,601 | Speedup tf tests | {
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"This single change made the tests on the TF CI pass from 6+ hours (non slow) to 29/31 minutes: https://github.com/huggingface/transformers/actions/runs/635711849\r\n\r\nWill look for a way to reduce their time."
] | 1,615 | 1,615 | 1,615 | MEMBER | null | Fyi @sgugger @patrickvonplaten @stas00, I'm temporarily marking these tests as slow as they take more than 1h30 minutes and prevent the CI from completing, therefore preventing any relevant information from the TF tests.
I'm working on improving the CI times so this is temporary (will revert by Friday). | {
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https://api.github.com/repos/huggingface/transformers/issues/10600 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10600/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10600/comments | https://api.github.com/repos/huggingface/transformers/issues/10600/events | https://github.com/huggingface/transformers/pull/10600 | 825,155,678 | MDExOlB1bGxSZXF1ZXN0NTg3Mjc3MzMz | 10,600 | [docs] How to solve "Title level inconsistent" sphinx error | {
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@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/10599 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10599/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10599/comments | https://api.github.com/repos/huggingface/transformers/issues/10599/events | https://github.com/huggingface/transformers/pull/10599 | 825,067,039 | MDExOlB1bGxSZXF1ZXN0NTg3MjAwMjAz | 10,599 | Pass encoder outputs into GenerationMixin | {
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"Hi @ymfa , thanks a lot for the PR!\r\n\r\n- The `generate` method does allow you to pass `input_embeds` as a keyword argument (`**model_kwargs` arg). If `input_embeds` is passed then T5 or any other model will use those instead of `input_ids`. If you look at the `generate` method signature, you can see that `inpu... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | # What does this PR do?
For encoder-decoder models such as T5, `GenerationMixin.generate()` currently runs both the encoder and the decoder. This PR allows one to pass already-computed `encoder_outputs` into this method, thus only the decoder will be run.
The flexibility to skip the encoder in the generation util... | {
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https://api.github.com/repos/huggingface/transformers/issues/10598 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10598/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10598/comments | https://api.github.com/repos/huggingface/transformers/issues/10598/events | https://github.com/huggingface/transformers/pull/10598 | 824,956,262 | MDExOlB1bGxSZXF1ZXN0NTg3MTA2ODM3 | 10,598 | Check layer types for Optimizer construction | {
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As pointed out on the [forum](https://discuss.huggingface.co/t/parameter-groups-and-gpt2-layernorm/4239), `Trainer` currently excludes form weight decay layernorm layers by using a name pattern, which is not consistently followed by all models.
This PR actual checks the layer types and add... | {
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https://api.github.com/repos/huggingface/transformers/issues/10597 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10597/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10597/comments | https://api.github.com/repos/huggingface/transformers/issues/10597/events | https://github.com/huggingface/transformers/issues/10597 | 824,950,439 | MDU6SXNzdWU4MjQ5NTA0Mzk= | 10,597 | No model card for roberta-large-finetuned-wsc | {
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"Are you talking about this model? https://huggingface.co/mrm8488/roberta-large-finetuned-wsc",
"> Are you talking about this model? https://huggingface.co/mrm8488/roberta-large-finetuned-wsc\r\n\r\nYes, this model i can not call by transformers. So how can i use it?",
"You can't call it from transformers? Do y... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
I can not finetune this model `roberta-large-finetuned-wsc`, it doesn't have model card.
## Your contribution
Please fix this!
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https://api.github.com/repos/huggingface/transformers/issues/10596 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10596/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10596/comments | https://api.github.com/repos/huggingface/transformers/issues/10596/events | https://github.com/huggingface/transformers/pull/10596 | 824,904,450 | MDExOlB1bGxSZXF1ZXN0NTg3MDYyNzk5 | 10,596 | Fairscale FSDP fix model save | {
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This PR fixes the fact training with fairscale fully-sharded wrapper was hanging: it looks like recent changes in fairscale make a synchronization during the model state dict call, which results in the training hanging if we don't call that state_dict method on all processes. This PR addresse... | {
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https://api.github.com/repos/huggingface/transformers/issues/10595 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10595/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10595/comments | https://api.github.com/repos/huggingface/transformers/issues/10595/events | https://github.com/huggingface/transformers/pull/10595 | 824,660,007 | MDExOlB1bGxSZXF1ZXN0NTg2ODU3NzIw | 10,595 | Fix version control with anchors | {
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In urls containing an anchor (such as https://huggingface.co/transformers/master/installation.html#caching-models), the version controller was not finding the right version (basically because the page wasn't ending with .html). This PR fixes that.
Fixes #10559 | {
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https://api.github.com/repos/huggingface/transformers/issues/10594 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10594/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10594/comments | https://api.github.com/repos/huggingface/transformers/issues/10594/events | https://github.com/huggingface/transformers/pull/10594 | 824,563,672 | MDExOlB1bGxSZXF1ZXN0NTg2Nzc2Mzc2 | 10,594 | [FeatureExtractorSavingUtils] Refactor PretrainedFeatureExtractor | {
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This PR refactors the class `PreTrainedFeatureExtractor`. The following changes are done to move functionality that is shared between sequence and image feature extractors into a separate file. This should unblock the PRs of [DETR](https://github.com/huggingface/transformers/pull/9998), [VIT]... | {
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https://api.github.com/repos/huggingface/transformers/issues/10593 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10593/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10593/comments | https://api.github.com/repos/huggingface/transformers/issues/10593/events | https://github.com/huggingface/transformers/pull/10593 | 824,500,587 | MDExOlB1bGxSZXF1ZXN0NTg2NzI1MDY2 | 10,593 | Enable torch 1.8.0 on GPU CI | {
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https://api.github.com/repos/huggingface/transformers/issues/10592 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10592/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10592/comments | https://api.github.com/repos/huggingface/transformers/issues/10592/events | https://github.com/huggingface/transformers/issues/10592 | 824,345,238 | MDU6SXNzdWU4MjQzNDUyMzg= | 10,592 | CUBLAS_STATUS_INTERNAL_ERROR at examples/question-answering/run_qa.py | {
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"Hi! I don't think torch supports CUDA 11.2 yet. See https://github.com/pytorch/pytorch/issues/50232#issuecomment-777703998",
"I had a similar issue with torch 1.8 and solved it by downgrading to 1.7.1",
"> Hi! I don't think torch supports CUDA 11.2 yet. See [pytorch/pytorch#50232 (comment)](https://github.com/... | 1,615 | 1,618 | 1,618 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.0.dev0
- Platform: Linux-5.10.20-1-lts-x86_64-with-glibc2.2.5
- Python version: 3.8.3
- PyTorch version ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10591 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10591/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10591/comments | https://api.github.com/repos/huggingface/transformers/issues/10591/events | https://github.com/huggingface/transformers/pull/10591 | 824,345,213 | MDExOlB1bGxSZXF1ZXN0NTg2NTk1NzA5 | 10,591 | Fix typo in docstring for pipeline | {
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Fixed typo in docstring for pipeline ("conversation" -> "conversational")
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Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflect... | {
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https://api.github.com/repos/huggingface/transformers/issues/10590 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10590/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10590/comments | https://api.github.com/repos/huggingface/transformers/issues/10590/events | https://github.com/huggingface/transformers/pull/10590 | 824,341,483 | MDExOlB1bGxSZXF1ZXN0NTg2NTkyNDY1 | 10,590 | [M2M100] fix positional embeddings | {
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The torchscript tests for `M2M100` are failing on master. This is because the `weights` in `M2M100SinusoidalPositionalEmbedding` are initially not on the same device as the rest of the parameters.
The PR makes the `weights` as `nn.Parameter` so they'll be on the same device. | {
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"Hi! In order to use either of those weights you'll have to convert them to a HuggingFace format.\r\n\r\nFor that you have two available scripts:\r\n- From [TF1](https://github.com/huggingface/transformers/blob/master/src/transformers/models/bert/convert_bert_original_tf_checkpoint_to_pytorch.py)\r\n- From [TF2](ht... | 1,615 | 1,619 | 1,619 | NONE | null | Hi everyone,
I was using BertForMaskedLM to predict possible candidate words in the content.
For example:
**cat like to drink [MASK], so am I.**
on [tf1 bert-pretrained model](https://storage.googleapis.com/bert_models/2018_10_18/uncased_L-12_H-768_A-12.zip)
output would be
`[[{'sequence': '[CLS] cat like ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10588 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10588/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10588/comments | https://api.github.com/repos/huggingface/transformers/issues/10588/events | https://github.com/huggingface/transformers/issues/10588 | 824,324,943 | MDU6SXNzdWU4MjQzMjQ5NDM= | 10,588 | Can't reproduce xlm-roberta-large finetuned result on XNLI | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,615 | 1,615 | 1,615 | NONE | null | # ❓ Questions & Help
I'm trying to finetune `xlm-roberta-large` on MNLI English training data and make zero-shot classification on XNLI dataset.
However, I found that `xlm-roberta-large` is super sensitive to hyper parameters. The reported average accuracy is 80.9, while my model can only achieve 79.74, which is 1%... | {
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https://api.github.com/repos/huggingface/transformers/issues/10587 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10587/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10587/comments | https://api.github.com/repos/huggingface/transformers/issues/10587/events | https://github.com/huggingface/transformers/pull/10587 | 824,304,025 | MDExOlB1bGxSZXF1ZXN0NTg2NTYwNDU3 | 10,587 | [WIP] Add Linformer | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,615 | 1,648 | null | CONTRIBUTOR | null | # What does this PR do?
This PR adds [Linformer: Self-Attention with Linear Complexity](https://arxiv.org/abs/2006.04768) by Facebook AI. Contrary to the regular Transformer, it has linear complexity in both space and time w.r.t. the sequence length, allowing it to be trained on much larger sequence lengths.
I'v... | {
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https://api.github.com/repos/huggingface/transformers/issues/10586 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10586/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10586/comments | https://api.github.com/repos/huggingface/transformers/issues/10586/events | https://github.com/huggingface/transformers/pull/10586 | 824,230,794 | MDExOlB1bGxSZXF1ZXN0NTg2NDk3Mjc4 | 10,586 | from_pretrained: check that the pretrained model is for the right model architecture | {
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"Hi @vimarshc, thank you for opening this PR! Could you:\r\n- rebase your PR on the most recent master so that the failing tests don't fail anymore\r\n- run `make fixup` at the root of your repository to fix your code quality issue (More information related to this on step 5 of [this document](https://github.com/hu... | 1,615 | 1,616 | 1,616 | CONTRIBUTOR | null | # What does this PR do?
Adding Checks to the from_pretrained workflow to check the model name passed belongs to the model being initiated.
Same checks need to be added for Tokenizer.
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in th... | {
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https://api.github.com/repos/huggingface/transformers/issues/10585 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10585/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10585/comments | https://api.github.com/repos/huggingface/transformers/issues/10585/events | https://github.com/huggingface/transformers/pull/10585 | 824,203,225 | MDExOlB1bGxSZXF1ZXN0NTg2NDc0MjA0 | 10,585 | [run_seq2seq] fix nltk lookup | {
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"I'm going to merge this since the issue could be interfering with other PRs."
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | Hmm, CI crashes every so often on
```
try:
nltk.data.find("tokenizers/punkt")
except LookupError:
```
introduced in this PR: https://github.com/huggingface/transformers/pull/10407
https://app.circleci.com/pipelines/github/huggingface/transformers/20635/workflows/989fde0b-e543-4620-9d9a-f213ad53dd9b/jobs... | {
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"It's still hanging waiting for something. If I'm not mistaken it's hanging in saving the model. but there is another thread that might be relevant:\r\n```\r\nThread 0x00007f6dd984b740 (most recent call first):\r\n File \"/home/stas/anaconda3/envs/main-38/lib/python3.8/site-packages/torch/_utils.py\", line 45 in _... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | This PR is fixing slow examples tests that currently fail on scheduled CI
2 more tests will be fixed by https://github.com/huggingface/transformers/pull/10551
This PR:
Sharded DDP issues:
* fixes fully sharded ddp enum - and the corresponding tests
* 2 sharded ddp tests currently hang with master fairscale -... | {
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```
trainer.train()
trainer.train()
```
under any environment that requires model wrapping - we currently get the wrapping multiple times - and things may kind of work - but most of the time it breaks badly - thanks to apex for complaining noisily when it's being wrapped second time.
i.e. ... | {
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# What does this PR do?
replace model used in Summarization example
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"Thanks to a fix for `timit_asr` that @patrickvonplaten made, now I have some good results using `wav2vec2-base`:\r\n\r\n<img width=\"1050\" alt=\"timit_asr_pr_ 10581\" src=\"https://user-images.githubusercontent.com/6879673/110573935-0435e480-8111-11eb-8e0e-845af4e2eab7.png\">\r\n\r\nI'm running one for `arabic_sp... | 1,615 | 1,616 | 1,616 | CONTRIBUTOR | null | # What does this PR do?
Building on #10145, I'm adding support for the two other speech datasets (besides LibriSpeech) for ASR at the time of writing (`timit_asr` and `arabic_speech_corpus`), which require the following:
* Custom validation split name
* On-the-fly resampling support to target feature extractor's sam... | {
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https://api.github.com/repos/huggingface/transformers/issues/10580 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10580/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10580/comments | https://api.github.com/repos/huggingface/transformers/issues/10580/events | https://github.com/huggingface/transformers/issues/10580 | 824,032,279 | MDU6SXNzdWU4MjQwMzIyNzk= | 10,580 | Issue when customizing loss in Trainer | {
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"I think you may be experiencing a bug that was fixed since then (I would need the whole error message to be sure) so before we dive further, could you see if an [install from source](https://huggingface.co/transformers/installation.html#installing-from-source) solves your problem?",
"Hi @sgugger,\r\n\r\nThank yo... | 1,615 | 1,615 | 1,615 | NONE | null | Hi everyone,
I am a student and therefore not yet very familiar with the way issues report work on git, so I aplogize in advance if this is not the proper place to post this message.
I'm trying to customize the loss to use a weighted CrossEntropyLoss, I browsed the issues reports and saw that this matter was alread... | {
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https://api.github.com/repos/huggingface/transformers/issues/10579 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10579/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10579/comments | https://api.github.com/repos/huggingface/transformers/issues/10579/events | https://github.com/huggingface/transformers/issues/10579 | 824,002,488 | MDU6SXNzdWU4MjQwMDI0ODg= | 10,579 | request about deepspeed tutorial | {
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"@dorost1234, thank you for the kind words. I'm glad to hear it was useful.\r\n\r\nIn general to answer the bulk of your questions - you will find the full documentation here:\r\nhttps://huggingface.co/transformers/master/main_classes/trainer.html#deepspeed\r\n\r\nPlease let me know if you still have any question a... | 1,615 | 1,619 | 1,619 | NONE | null | Dear @stas00
You have created this great tutorial here that without you it was really very hard near impossible to be able to train these large models, thank you so much
https://github.com/huggingface/transformers/issues/8771
Do you mind updating your comment, including how numbers would change if you add di... | {
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https://api.github.com/repos/huggingface/transformers/issues/10578 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10578/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10578/comments | https://api.github.com/repos/huggingface/transformers/issues/10578/events | https://github.com/huggingface/transformers/issues/10578 | 823,987,220 | MDU6SXNzdWU4MjM5ODcyMjA= | 10,578 | Why HFArgumentParser.parse_dict(TrainerArguments) return tuple instead of dict? | {
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"hi @akalieren \r\n\r\nthe `parse_dict` or `parse_args_into_dataclasses` methods always return a `tuple` of parsed arguments for each `dataclass` that was used to initialize `HfArgumentParser`. Here you're initializing it with just `TrainingArguments` so `parse_dict` returns a `tuple` of length 1.\r\n\r\nHope this... | 1,615 | 1,615 | 1,615 | NONE | null | I guess it is not certainly bug however I could not almost understand why` HfArgumentParser.parsedict() `return `(*outputs,)`. As can be seen in [docs](https://huggingface.co/transformers/_modules/transformers/hf_argparser.html#HfArgumentParser
)
I am trying to fine-tune BERT for Token Classification using Trainer cl... | {
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https://api.github.com/repos/huggingface/transformers/issues/10577 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10577/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10577/comments | https://api.github.com/repos/huggingface/transformers/issues/10577/events | https://github.com/huggingface/transformers/issues/10577 | 823,986,008 | MDU6SXNzdWU4MjM5ODYwMDg= | 10,577 | seq2seq example with T5 does not run due to issue with loading tokernizer | {
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"solved with installing sentencepiece, I appreciate adding a file mentioning requirements.txt thanks ",
"Hi @dorost1234 ,\r\nGlad you resolved the issue. Your `transformers` version is old, we have now added the `sentencepiece` dependency in `requirements.txt`.\r\nhttps://github.com/huggingface/transformers/blob... | 1,615 | 1,615 | 1,615 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.3
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): - ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10576 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10576/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10576/comments | https://api.github.com/repos/huggingface/transformers/issues/10576/events | https://github.com/huggingface/transformers/issues/10576 | 823,984,867 | MDU6SXNzdWU4MjM5ODQ4Njc= | 10,576 | Movement pruning for DistilGPT2 - pre_trained model, issue while using dynamic_quantization | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,615 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Ubuntu 20.04
- Python version: 3.8.8
- PyTorch version (GPU?): 1.4.0 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: False
- Using distributed or parallel set-up in script?: False
### Who can help
[@VictorSanh](htt... | {
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https://api.github.com/repos/huggingface/transformers/issues/10575 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10575/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10575/comments | https://api.github.com/repos/huggingface/transformers/issues/10575/events | https://github.com/huggingface/transformers/issues/10575 | 823,979,670 | MDU6SXNzdWU4MjM5Nzk2NzA= | 10,575 | bug in run_finetune | {
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"sorry my mistake to use last version of examples ",
"hi how you solved this. i also face this error. i can't find \"is_offline_mode\" and \"get_full_repo_name\" under transformers.utils. i use https://github.com/huggingface/transformers/tree/main/examples/pytorch/summarization",
"This should work if you are u... | 1,615 | 1,700 | 1,615 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.3
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): -... | {
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https://api.github.com/repos/huggingface/transformers/issues/10574 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10574/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10574/comments | https://api.github.com/repos/huggingface/transformers/issues/10574/events | https://github.com/huggingface/transformers/issues/10574 | 823,933,972 | MDU6SXNzdWU4MjM5MzM5NzI= | 10,574 | The dimension of Feature extraction | {
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"How did you create the `nlp_features` function?\r\n\r\nThe sequence length is different due to different tokenization. ",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that iss... | 1,615 | 1,619 | 1,619 | NONE | null |
why this happened?
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https://api.github.com/repos/huggingface/transformers/issues/10573 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10573/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10573/comments | https://api.github.com/repos/huggingface/transformers/issues/10573/events | https://github.com/huggingface/transformers/pull/10573 | 823,862,909 | MDExOlB1bGxSZXF1ZXN0NTg2MjEwOTE4 | 10,573 | Update data_collator.py | {
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https://api.github.com/repos/huggingface/transformers/issues/10572 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10572/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10572/comments | https://api.github.com/repos/huggingface/transformers/issues/10572/events | https://github.com/huggingface/transformers/issues/10572 | 823,851,373 | MDU6SXNzdWU4MjM4NTEzNzM= | 10,572 | Import error for class Speech2TextProcessor, Speech2TextTransformerForConditionalGeneration | {
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"hi @amiyamandal-dev \r\nThank you for your interest in `S2T`. It's still a work in progress and not available on master yet. If you want to try it, you could checkout this PR #10175",
"Hey @amiyamandal-dev ,\r\n\r\nThe model is now available on [master](https://huggingface.co/transformers/master/model_doc/speech... | 1,615 | 1,615 | 1,615 | NONE | null | ## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.8
- PyTorch version (GPU?): 1.7.1+cpu (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>
### ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10571 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10571/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10571/comments | https://api.github.com/repos/huggingface/transformers/issues/10571/events | https://github.com/huggingface/transformers/issues/10571 | 823,820,617 | MDU6SXNzdWU4MjM4MjA2MTc= | 10,571 | Advice on creating/wrapping `PreTrainedModel` to be compatible with the codebase? | {
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"Hey @HanGuo97,\r\n\r\nWe try to keep the GitHub issues for bug reports. Do you mind asking your question on the forum instead? Also there might already be similar questions on the forum, such as https://discuss.huggingface.co/t/create-a-custom-model-that-works-with-any-pretrained-transformer-body/4186. Thanks!",
... | 1,615 | 1,615 | 1,615 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: NA
- Platform: NA
- Python version: NA
- PyTorch version (GPU?): NA
- Tensorflow version (GPU?): NA
- Usin... | {
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https://api.github.com/repos/huggingface/transformers/issues/10570 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10570/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10570/comments | https://api.github.com/repos/huggingface/transformers/issues/10570/events | https://github.com/huggingface/transformers/pull/10570 | 823,812,800 | MDExOlB1bGxSZXF1ZXN0NTg2MTc1ODY1 | 10,570 | fix tf doc bug | {
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I Have create a forum at `https://discuss.huggingface.co/t/different-doc-with-bertforpretraining-and-tfbertforpretraining/4167` and get a response.
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Also rewrote the test to be more readable. Could test TF/Flax too but I don't have tiny models to run quick tests on.
@Lys... | {
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"Thank you for addressing this! I left some minor comments/questions.",
"@LysandreJik I think this is ready for review now.",
"Hey @elk-cloner, @francescorubbo! That's an amazing work you've done here. The added tests are a wonderful addition, and will ensure the pipeline is as robust as it can be.\r\n\r\nTo ma... | 1,615 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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"Apparently, someone [just did it](https://huggingface.co/facebook/wav2vec2-large-xlsr). But there are some files missing and it currently unusable. Hopefully the author will soon update it :)",
"Pinging @patrickvonplaten for knowledge :)",
"Yeah, I just added the pretrained checkpoint. I'll release a notebook ... | 1,615 | 1,631 | 1,631 | NONE | null | # 🚀 Feature request
Is it possible to use XLSR-53 with transformers in the near future?
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"Duplicate of https://github.com/huggingface/transformers/issues/8933 . This wrong waring should have been fixed in newer versions, see: https://github.com/huggingface/transformers/blob/63c295ac05962b03701bdda87a90595b5f864075/src/transformers/models/t5/modeling_t5.py#L1188",
"Great! So *all* weights are in fact ... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.0.1
- Platform: Linux-4.15.0-132-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1+cu110 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: ... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,615 | 1,619 | 1,619 | NONE | null | Code to reproduce
```python
tokenizer = get_fsmt_tokenizer()
tokenizer.model_max_length=100
model = get_fsmt_model()
freeze_embeds(model)
freeze_encoder(model)
train_dataset = YandexRuEnDataset("data", split="train")
val_dataset = YandexRuEnDataset("data", split="valid")
traini... | {
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"This is not a problem.\r\nWhen the model predicts the word next to \"Ich\" (given \"Ich\"), the word \"Ich\" cannot attend the words in the future positions (e.g., \"will\", \"ein\", etc).\r\nHowever, when the model predicts the word next to \"ein\" (given \"Ich will ein\"), the word \"Ich\" can attend \"will\" an... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | # Problem
Causal Models is only attended to the left context. Therefore causal models should not depend on the right tokens.
For example, The word embedding of "I" will be unchanged no matter what is in the right In GPT2. Since Causal Language Model are uni-directional self-attention.
```
from transformers impo... | {
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## code info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
here's my model:
![image](https://user-images.githubusercontent.com/56223656/110211963-61276580-7e99-11eb-8508-42591b5138e6.png... | {
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"@stas00, @sgugger, please review this PR. Here is a visualization of what would be done by the bot, were it to be merged today: https://github.com/huggingface/transformers/pull/10562/checks?check_run_id=2113061781\r\n\r\nI have verified that all 11 issues that would be closed have received a warning 10 days ago. T... | 1,615 | 1,618 | 1,618 | MEMBER | null | This is an updated version of the stale bot.
**It is easier to review the file than the diff, you can find the file [here](https://github.com/huggingface/transformers/blob/d1e516ea0fe9e641a75a89e5a7522392f7dbd59d/scripts/stale.py).**
It sends a warning message after 23 days of inactivity, and closes the issue/PR ... | {
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This PR:
* fixes a few tests to make them run on multi-gpu
* removes the decorator where it's not needed after testing that it works
* leaves t... | {
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"Pinging @JetRunner ",
"@stas00 Well it is just not designed for DP or DDP. DeeBERT is for accelerating inference with bs=1 (especially on CPU). I don't believe it should support DP.",
"But yes theoretically it can support multi-GPU training but I'm not sure if it's necessary?",
"That's good enough for me, I ... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | I'm working on making the tests work under multiple gpus and run into and this one that proved to be stubborn, for some reason it doesn't work under any DP scheme. I don't know anything about this script, To reproduce:
Note - you need at least 2 gpus:
Actually it fails with 1 gpu too (just change to --nproc_per_n... | {
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https://huggingface.co/transformers/master/installation.html#caching-models
upper left corner - if you want to switch to a different branch it sends you to a 404 page on all of them:
it has an issue with the base url, no... | {
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"Hi @j2538318409,\r\n\r\nI think Mbart model from facebook can do that for you [mbart](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt), \r\n\r\nYou need to specify `zh_CN` as the source language and `en_XX` as the target language.\r\n\r\n This [colab notebook](https://github.com/bhadreshpsavani/Und... | 1,614 | 1,619 | 1,619 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
<!-- Please outline the motivation for the proposal. Is your feature request
related to a problem? e.g., I'm always frustrated when [.... | {
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"Pinging @lhoestq and @patrickvonplaten ",
"Hello there,\r\n\r\nI am having the exact same issue when trying to finetune rag. I used the masters version of transformers.\r\n\r\nI tried a couple of different things like:\r\n - My own dataset and wikipedia default one\r\n - In a physical machine and in colab\r\n - ... | 1,614 | 1,617 | 1,616 | NONE | null | Hi there.
Perhaps the following isn’t even a real issue, but I’m a bit confused with the current outputs I got.
I’m trying to fine tune RAG on a bunch of question-answer pairs I have (for while, not that much, < 1k ones). I have splitted them as suggested (train.source, train.target, val.source…). After running ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10556 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10556/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10556/comments | https://api.github.com/repos/huggingface/transformers/issues/10556/events | https://github.com/huggingface/transformers/pull/10556 | 823,500,968 | MDExOlB1bGxSZXF1ZXN0NTg1OTUwMjQ4 | 10,556 | Layoutlm tf | {
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"Oh, no! Did you have some issues with a rebase? Can we help in any way?",
"> Oh, no! Did you have some issues with a rebase? Can we help in any way?\r\n\r\nI do! For some reason when I rebased I was not able to push my changes. It was rejected because my branch was diverged too much form the remote. Then my opti... | 1,614 | 1,615 | 1,615 | CONTRIBUTOR | null | # What does this PR do?
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"This kind of logging is very useful for researchers. Let's add them back?\r\n\r\nhttps://github.com/google-research/bert/blob/master/run_classifier.py#L871",
"In a nutshell, I'll burst into tears if we can just have Google's `run_classifier.py` back but with `accelerate` :)",
"Maybe we should tag other researc... | 1,614 | 1,615 | 1,615 | COLLABORATOR | null | # What does this PR do?
This PR adds a new GLUE example that does not use the `Trainer`, leveraging [accelerate](https://github.com/huggingface/accelerate) for the distributed training. The necessary instructions are added in the text-classification README.
cc @JetRunner as it should be of interest to you. | {
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"Some tests failed due to pad_token_id being None. Is this really a possibility for any Transformer model?",
"Added a check for `token_pad_id` equal to `None` and tests pass, but it is not very elegant, any feedback will be appreciated.",
"I just noticed that one test, `run_tests_flax`, failed, however no chang... | 1,614 | 1,616 | 1,616 | NONE | null | # What does this PR do?
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"Thank you for having a closer look that I did, @sgugger.\r\n\r\nIdeally we should have tests that would have caught this",
"Hi @stas00,\r\n\r\nHow can we add test cases for this testing? If we check `max_train_samples` and `max_valid_samples` from metrics and add assert statement that might be possible.\r\n ",
... | 1,614 | 1,615 | 1,615 | CONTRIBUTOR | null | # What does this PR do?
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"cc @sgugger ",
"Yes there is nothing available for that right now. I believe the to `run_hp_search` functions should save the checkpoints of the non-aborted training and at least return the location of the best checkpoint in the BestRun namedtuple, as well as load the best model fine-tuned at the end if `load_be... | 1,614 | 1,619 | 1,619 | NONE | null | Hi,
after doing a hyperparameter search(by calling `hyperparameter_search`on the trainer object) , I asked myself how to easily get the best model out of it. Currently, I'm using Ray Tune as a backend.
Given [the code in integrations.py](https://github.com/huggingface/transformers/blob/54e55b52d4886d4c63e592310b425... | {
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This PR fixes several embeddings layer with the recent breaking change introduced in PyTorch 1.8. Up until PyTorch 1.7, the `padding_idx` passed to an embedding layer was used to initialize the corresponding row in the weights to 0 but ignored afterwards.
Now, this `padding_idx` is used at... | {
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"Thanks for flagging! Do you want to make a PR to fix it?",
"> Thanks for flagging! Do you want to make a PR to fix it?\r\n\r\nI tried (#10554). Did I do it correctly?",
"Looks okay to me! Let's just wait to check the tests pass. Thanks! :-)"
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | I noticed the hyperlink to the documentation of optuna's create_study under ```kwargs``` in the ```hyperparameter_search``` method of Trainer is outdated.
https://huggingface.co/transformers/main_classes/trainer.html
### Who can help
Documentation: @sgugger
New URL (I'm guessing): https://optuna.readthedocs.... | {
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https://api.github.com/repos/huggingface/transformers/issues/10543 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10543/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10543/comments | https://api.github.com/repos/huggingface/transformers/issues/10543/events | https://github.com/huggingface/transformers/issues/10543 | 823,022,900 | MDU6SXNzdWU4MjMwMjI5MDA= | 10,543 | Similar issue like #1091 in Blenderbot | {
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"Do you encounter any errors because of the mismatch in length?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](http... | 1,614 | 1,619 | 1,619 | NONE | null | Tokenizer and model are not in sync. I am using "facebook/blenderbot-400M-distill"
Tokenizer has 8009 base tokens where as model has 8008.
Could you please help me with this?
`from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
mname = "facebook/blenderbot-400M-distill"
mod... | {
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https://api.github.com/repos/huggingface/transformers/issues/10542 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10542/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10542/comments | https://api.github.com/repos/huggingface/transformers/issues/10542/events | https://github.com/huggingface/transformers/issues/10542 | 823,012,844 | MDU6SXNzdWU4MjMwMTI4NDQ= | 10,542 | OSError: Can't load weights for 'facebook/mbart-large-cc25' when using TFMBartModel | {
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"Hi! Yes, you can load the PyTorch weights into a Transformer model by adding `from_pt=True` in the `from_pretrained` method.",
"Thank you very much @LysandreJik!\r\nI have tried two ways:\r\n\r\n**Option 1 Using from_pt = True**\r\n_bart_model = TFMBartModel.from_pretrained(\"facebook/mbart-large-cc25\", from_pt... | 1,614 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Windows 10
- Python version: 3.8
- PyTorch version (GPU?): - No
- Tensorflow version (GPU?): 2.4.1, Yes
- Using GPU in script?: Yes (I think it is indifferent for this issue)
- Using distributed or parallel set-up in script?: No
## Issue Descri... | {
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https://api.github.com/repos/huggingface/transformers/issues/10541 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10541/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10541/comments | https://api.github.com/repos/huggingface/transformers/issues/10541/events | https://github.com/huggingface/transformers/issues/10541 | 822,953,463 | MDU6SXNzdWU4MjI5NTM0NjM= | 10,541 | Facing Issue while running `run_tf_multiple_choice.py` from examples | {
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"Even for the `run_tf_squad.py` script, I am facing the issue. \r\n\r\nHere is the [colab notebook](https://github.com/bhadreshpsavani/UnderstandingNLP/blob/master/Check_run_tf_squad.ipynb) with issue and Traceback logs\r\n\r\nIs there anything else I need to use while running the script?",
"Hello!\r\n\r\nThe mu... | 1,614 | 1,615 | 1,615 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.0.dev0
- Platform: Colab
- Python version: NA
- PyTorch version (GPU?): NA
- Tensorflow version (GPU?):... | {
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https://api.github.com/repos/huggingface/transformers/issues/10540 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10540/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10540/comments | https://api.github.com/repos/huggingface/transformers/issues/10540/events | https://github.com/huggingface/transformers/issues/10540 | 822,934,560 | MDU6SXNzdWU4MjI5MzQ1NjA= | 10,540 | 🐛 Bug in attention head mask for cross-attention module in encoder-decoder models | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,614 | 1,619 | 1,619 | CONTRIBUTOR | null | Currently, encoder-decoder models use either `head_mask` or `decoder_head_mask` for masking attention heads in cross-attention modules. Both cases are not perfectly correct. Furthermore, MHA in cross-attention modules shares the parameters with the decoder, i.e. `shape = (decoder.num_layers, decoder.num_attention_heads... | {
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https://api.github.com/repos/huggingface/transformers/issues/10539 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10539/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10539/comments | https://api.github.com/repos/huggingface/transformers/issues/10539/events | https://github.com/huggingface/transformers/issues/10539 | 822,912,158 | MDU6SXNzdWU4MjI5MTIxNTg= | 10,539 | Wave2vec custom training tokenizer bug | {
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"I will add a notebook on how to fine-tune Wav2Vec2 on languages other than English next week (think I'll also go for the German Common Voice dataset). We only today added the multi-lingual checkpoint, so you probably used the English checkpoint which cannot handle German. If you didn't see the notebook within ~1,2... | 1,614 | 1,616 | 1,615 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: master
- Platform: win 10
- Python version: 3.8
- PyTorch version (GPU?): GPU
- Tensorflow version (GPU?):
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10538 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10538/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10538/comments | https://api.github.com/repos/huggingface/transformers/issues/10538/events | https://github.com/huggingface/transformers/issues/10538 | 822,904,612 | MDU6SXNzdWU4MjI5MDQ2MTI= | 10,538 | Transfomer-xl padding token | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,614 | 1,614 | 1,614 | NONE | null | When dealing with a batch consisting of sequences of different lengths, how do I choose parameters so that padding_token is not involved in the computation. | {
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https://api.github.com/repos/huggingface/transformers/issues/10537 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10537/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10537/comments | https://api.github.com/repos/huggingface/transformers/issues/10537/events | https://github.com/huggingface/transformers/pull/10537 | 822,904,187 | MDExOlB1bGxSZXF1ZXN0NTg1NDUwNjcx | 10,537 | Fix example of custom Trainer to reflect signature of compute_loss | {
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"Not sure why the tests are failing since I only tweaked the docs - perhaps it's a problem with the CI on your end?"
] | 1,614 | 1,614 | 1,614 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/10536 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10536/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10536/comments | https://api.github.com/repos/huggingface/transformers/issues/10536/events | https://github.com/huggingface/transformers/pull/10536 | 822,876,096 | MDExOlB1bGxSZXF1ZXN0NTg1NDI3NzM3 | 10,536 | Enabling multilingual models for translation pipelines. | {
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"@LysandreJik \r\n\r\nI added a method here `deep_round` to try and make test equality a bit sane.\r\n\r\ntorchTensor(...) == torch.Tensor(..) does not work (understandably).\r\nAny sort of float comparison is also flaky.\r\n\r\n`deep_round` simply tries to make `assertEqual` work in a sane way for any sort of nest... | 1,614 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
Enables mutlilingual translation for pipelines.
Some models can target multiple languages/ language pairs. Before this PR, there was no simple way to exploit that within the Translation pipeline.
## Move away from `translation_XX_to_YY`.
Because src_lang, tgt_lang pairs can be used f... | {
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